In [3]:
# Reproject trapezoidal tray to rectangular (rectify)
img = cv2.cvtColor(cv2.imread('test.png'), cv2.COLOR_BGR2RGB)
masks = SamAutomaticMaskGenerator(
model=sam,
points_per_side=32, # The number of points to be sampled along one side of the image
min_mask_region_area=100, # If >0, postprocessing will be applied to remove disconnected regions and holes in masks with area smaller than min_mask_region_area
).generate(img)
tray = max(masks, key=lambda x: x["area"])
# Convert binary mask to polygon
tray = shape(next(shapes(tray["segmentation"].astype(np.uint8), mask=tray["segmentation"]))[0])
plt.figure(figsize=(10,10))
plt.imshow(img)
trapezoid = tray.convex_hull.simplify(50).exterior
bounds = box(*tray.bounds).exterior
gpd.GeoSeries(trapezoid).plot(ax=plt.gca(), color="red")
gpd.GeoSeries(bounds).plot(ax=plt.gca(), color="green")
plt.show()
source_corners = np.float32(sorted(trapezoid.coords[:4]))
target_corners = np.float32(sorted(bounds.coords[:4]))
matrix = cv2.getPerspectiveTransform(source_corners, target_corners)
print(matrix)
img = cv2.warpPerspective(img, matrix, (img.shape[1], img.shape[0]), cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0))
plt.figure(figsize=(10,10))
plt.imshow(img)
[[ 7.71693934e-01 4.00033953e-04 -5.33633167e+00] [-1.14264902e-01 -9.79087398e-01 9.10024367e+02] [-3.34754835e-04 -8.87150418e-05 1.00000000e+00]]
Out[3]:
<matplotlib.image.AxesImage at 0x7f73fa607a90>
